In general, conventional data compression includes encoding information using fewer bits than a respective original bit representation. Thus, conventional data compression techniques have been used to reduce data storage requirements associated with corresponding content.
Data compression can be lossy or lossless. For example, as its name suggests, lossy compression includes removing less needed bit information during compression. When decompressing data compressed using a lossy compression algorithm, the removed bit information is lost and cannot be retrieved. In certain instances, loss of a small amount of data may not be particularly important when reproducing a rendition of an original signal or image.
Lossless compression may be more desirable over lossy compression because it may be undesirable to lose bit information upon reconstruction of a rendition of the original data.
It is sometimes desirable to compress event data obtained in a cable network environment. For example, a cable network environment may include many subscribers that tune to different content available over many different available channels. Log information collected in the cable network environment can specify which content subscriber's select for consumption. Typically, keeping track of tuning information for many subscribers over many different viewable channels produces an inordinate amount of data to manage.
As discussed above, content consumption information can be compressed using conventional algorithms. However, even standard compression of content consumption information can require a large amount of storage capacity to store respective data.